Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/66024
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Building Services Engineering | en_US |
dc.creator | Cheng, Q | en_US |
dc.creator | Wang, S | en_US |
dc.creator | Yan, C | en_US |
dc.date.accessioned | 2017-05-22T02:09:35Z | - |
dc.date.available | 2017-05-22T02:09:35Z | - |
dc.identifier.issn | 0360-5442 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/66024 | - |
dc.language.iso | en | en_US |
dc.publisher | Pergamon Press | en_US |
dc.rights | © 2016 Elsevier Ltd. All rights reserved. | en_US |
dc.rights | © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/ | en_US |
dc.rights | The following publication Cheng, Q., Wang, S., & Yan, C. (2017). Sequential Monte Carlo simulation for robust optimal design of cooling water system with quantified uncertainty and reliability. Energy, 118, 489-501 is available at https://doi.org/10.1016/j.energy.2016.10.051 | en_US |
dc.subject | Cooling water system | en_US |
dc.subject | Reliability | en_US |
dc.subject | Robust optimal design | en_US |
dc.subject | Sequential Monte Carlo simulation | en_US |
dc.subject | Uncertainty-based design | en_US |
dc.title | Sequential Monte Carlo simulation for robust optimal design of cooling water system with quantified uncertainty and reliability | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 489 | en_US |
dc.identifier.epage | 501 | en_US |
dc.identifier.volume | 118 | en_US |
dc.identifier.doi | 10.1016/j.energy.2016.10.051 | en_US |
dcterms.abstract | Conventional design of cooling water systems mainly focused on the individual components of cooling water system, not the system as a whole. In this paper, a robust optimal design based on sequential Monte Carlo simulation is proposed to optimize the design of cooling water system. Monte Carlo simulation is used to obtain the cooling load distribution of required accuracy, power consumption and unmet cooling load. Convergence assessment is conducted to terminate the sampling process of Monte Carlo simulation. Under different penalty ratios and repair rates, this proposed design minimizes the annual total cost of cooling water system. A case study of a building in Hong Kong is conducted to demonstrate the design process and test the robust optimal design method. The results show that the minimum total cost could be achieved under various possible cooling load conditions considering the uncertainties of design inputs and reliability of system components. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Energy, 1 Jan. 2017, v. 118, p. 489-501 | en_US |
dcterms.isPartOf | Energy | en_US |
dcterms.issued | 2017-01-01 | - |
dc.identifier.scopus | 2-s2.0-85010657691 | - |
dc.identifier.ros | 2016005673 | - |
dc.identifier.eissn | 1873-6785 | en_US |
dc.identifier.rosgroupid | 2016005422 | - |
dc.description.ros | 2016-2017 > Academic research: refereed > Publication in refereed journal | en_US |
dc.description.validate | 201804_a bcma | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | RGC-B3-0548, BEEE-0714 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | MTR Corporation Limited | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 6718064 | - |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Wang_Sequential_Monte_Carlo.pdf | Pre-Published version | 1.98 MB | Adobe PDF | View/Open |
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